Alexander Terenin is a Ph.D. student in statistics and applied mathematics at the University of California, Santa Cruz. His research focuses on Bayesian statistics at scale, especially Markov Chain Monte Carlo methods in novel hardware environments such as compute clusters and GPUs that are found in the big data setting. Prior to attending UCSC, he completed his bachelor's degree with a double major in statistics and psychology at the University of California, Santa Barbara, where he graduated with highest honors and was selected to be commencement speaker at graduation. His data science experience includes over a year at eBay, Inc., where he worked on natural language processing tasks for improving its search engine. He is the author of three papers available on arXiv and currently under review, and has given five presentations at leading international research conferences in statistics.